Premium Content

Access "Should in-memory analysis have a seat at your big data table?"

Published: 09 Sep 2013

In-memory processing can serve as a high-octane fuel for supercharging big data analytics applications. But organizations should weigh factors such as additional systems infrastructure costs and the readiness of their business processes before gassing up with in-memory analytics technology. Another key step in greasing the deployment skids is identifying big data analytics problems that have proven unsolvable or that could benefit from the performance boost typically provided by in-memory analysis applications. "The integration of in-memory capabilities and big data boils down to use case and benefits," said Paul Barth, co-founder of data management and analytics consultancy NewVantage Partners. "You need to consider the business value of accelerating time to answer -- is it a matter of convenience, or is it a case when rapid turnaround and rapid analysis really benefits the decision-making process." Detecting patterns in large stockpiles of data is one application where using in-memory analytics tools makes sense, Barth said, as are scenarios in which ... Access >>>

Access TechTarget
Premium Content for Free.

By submitting you agree to receive email from TechTarget and its partners. If you reside outside of the United States, you consent to having your personal data transferred to and processed in the United States. Privacy

What's Inside

Features

More Premium Content Accessible For Free

  • New talent management software transforming HR
    BI_0814.png
    E-Zine

    Human resources departments have long been associated with rubber stamps and reams of paper forms. But new talent management software -- technology ...

  • Determine if NoSQL databases are right for your organization
    NoSQL_software_adds_database_choices.PNG
    E-Handbook

    NoSQL databases offer more flexible alternatives to mainstream relational software, particularly for big data applications. But NoSQL offerings ...

  • Build today for tomorrow's big data architectures
    big_data_future.png
    E-Handbook

    Developing a big data architecture today involves pulling together a lot of different technology pieces. The prevalence of unstructured data has ...